PURPOSE: To investigate the potential clinical relevance of a new algorithm to remove muscle artifacts in ictal scalp EEG. METHODS: Thirty-seven patients with refractory partial epilepsy with a well-defined seizure onset zone based on full presurgical evaluation, including SISCOM but excluding ictal EEG findings, were included. One ictal EEG of each patient was presented to a clinical neurophysiologist who was blinded to all other data. Ictal EEGs were first rated after band-pass filtering, then after elimination of muscle artifacts using a blind source separation-canonical correlation analysis technique (BSS-CCA). Degree of muscle artifact contamination, lateralization, localization, time and pattern of ictal EEG onset were compared between the two readings and validated against the other localizing information. RESULTS: Muscle artifacts contaminated 97% of ictal EEGs, and interfered with the interpretation in 76%, more often in extratemporal than temporal lobe seizures. BSS-CCA significantly improved the sensitivity to localize the seizure onset from 62% to 81%, and performed best in ictal EEGs with moderate to severe muscle artifact contamination. In a significant number of the contaminated EEGs, BSS-CCA also led to an earlier identification of ictal EEG changes, and recognition of ictal EEG patterns that were hidden by muscle artifact. CONCLUSIONS: Muscle artifacts interfered with the interpretation in a majority of ictal EEGs. BSS-CCA reliably removed these muscle artifacts in a user-friendly manner. BSS-CCA may have an important place in the interpretation of ictal EEGs during presurgical evaluation of patients with refractory partial epilepsy.
PURPOSE: To investigate the potential clinical relevance of a new algorithm to remove muscle artifacts in ictal scalp EEG. METHODS: Thirty-seven patients with refractory partial epilepsy with a well-defined seizure onset zone based on full presurgical evaluation, including SISCOM but excluding ictal EEG findings, were included. One ictal EEG of each patient was presented to a clinical neurophysiologist who was blinded to all other data. Ictal EEGs were first rated after band-pass filtering, then after elimination of muscle artifacts using a blind source separation-canonical correlation analysis technique (BSS-CCA). Degree of muscle artifact contamination, lateralization, localization, time and pattern of ictal EEG onset were compared between the two readings and validated against the other localizing information. RESULTS: Muscle artifacts contaminated 97% of ictal EEGs, and interfered with the interpretation in 76%, more often in extratemporal than temporal lobe seizures. BSS-CCA significantly improved the sensitivity to localize the seizure onset from 62% to 81%, and performed best in ictal EEGs with moderate to severe muscle artifact contamination. In a significant number of the contaminated EEGs, BSS-CCA also led to an earlier identification of ictal EEG changes, and recognition of ictal EEG patterns that were hidden by muscle artifact. CONCLUSIONS: Muscle artifacts interfered with the interpretation in a majority of ictal EEGs. BSS-CCA reliably removed these muscle artifacts in a user-friendly manner. BSS-CCA may have an important place in the interpretation of ictal EEGs during presurgical evaluation of patients with refractory partial epilepsy.
Authors: M Al Harrach; S Boudaoud; M Hassan; F S Ayachi; D Gamet; J F Grosset; F Marin Journal: Med Biol Eng Comput Date: 2016-05-25 Impact factor: 2.602
Authors: Walter G Besio; Iris E Martínez-Juárez; Oleksandr Makeyev; John N Gaitanis; Andrew S Blum; Robert S Fisher; Andrei V Medvedev Journal: IEEE J Transl Eng Health Med Date: 2014-06-30 Impact factor: 3.316
Authors: Samuel Boudet; Laurent Peyrodie; William Szurhaj; Nicolas Bolo; Antonio Pinti; Philippe Gallois Journal: ScientificWorldJournal Date: 2014-09-14